CN114331826A - Fisheye image rapid correction method based on distortion tension factor - Google Patents
Fisheye image rapid correction method based on distortion tension factor Download PDFInfo
- Publication number
- CN114331826A CN114331826A CN202210062723.9A CN202210062723A CN114331826A CN 114331826 A CN114331826 A CN 114331826A CN 202210062723 A CN202210062723 A CN 202210062723A CN 114331826 A CN114331826 A CN 114331826A
- Authority
- CN
- China
- Prior art keywords
- image
- distortion
- fisheye image
- correction
- fisheye
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012937 correction Methods 0.000 title claims abstract description 74
- 238000000034 method Methods 0.000 title claims abstract description 39
- 238000013507 mapping Methods 0.000 claims abstract description 25
- 238000005457 optimization Methods 0.000 claims description 13
- 238000000605 extraction Methods 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 2
- 238000003702 image correction Methods 0.000 abstract description 12
- 230000000694 effects Effects 0.000 abstract description 4
- 239000000284 extract Substances 0.000 abstract 1
- 238000003384 imaging method Methods 0.000 description 3
- 230000009466 transformation Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 241000251468 Actinopterygii Species 0.000 description 1
- 238000012935 Averaging Methods 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 230000001131 transforming effect Effects 0.000 description 1
Images
Landscapes
- Image Processing (AREA)
Abstract
The invention discloses a fisheye image fast correction method based on distortion tension factors, which extracts an effective area of a fisheye image; establishing a fisheye image correction model based on a distortion stretching factor on the basis of a longitude correction model; and determining the value of a distortion stretching factor in the model, establishing a mapping relation between pixel coordinates in a blank corrected image and sub-pixel coordinates of an effective area of the fisheye image, completing coordinate mapping and gray interpolation, and obtaining a corresponding corrected image of the fisheye image. The fisheye image correction method based on the radial distortion effect is used for correcting fisheye images in the transverse direction and the longitudinal direction on the basis of considering the radial distortion effect, has the characteristics of simple algorithm, strong real-time performance, easiness in transplanting embedded equipment and mobile equipment, and is good in correction effect.
Description
Technical Field
The invention relates to the technical field of digital image processing, in particular to a fisheye image rapid correction method.
Background
The range of the shooting angle of view of the lens adopted by a common camera is relatively small, and a fisheye lens can be used for reflecting all content information of a shot scene. The fisheye lens is a short-focus and large-visual-angle (the visual angle is between 180 degrees and 270 degrees) lens, and by utilizing the characteristic that the visual angle is large, the fisheye lens can be used for shooting to obtain a fisheye image containing larger information content than an image shot by using a common camera, and the fisheye lens does not need to rotate and scan when the camera works, so that the fisheye lens is small in size and convenient and simple to use. Therefore, the fisheye lens is widely used for quality inspection in a narrow space or a region where a spatial position is limited.
The fisheye lens can obtain a larger view angle range than that of a general camera because of the difference in lens models therebetween. Most lenses are designed according to a pinhole camera model, according to the fact that light rays are transmitted along a straight line direction, the intersection point of two straight lines is still the point where the two straight lines intersect after transformation, namely the geometric property is kept unchanged, and therefore a shot image can be closely related to an original scene. However, the lens under this model has a drawback that the light rays always travel along a straight line, which makes it difficult for the lens to capture objects located at the edge of the scene. In the case of the limited size of the negative film (CMOS), the fisheye lens can capture more scenes at the edge than the lens of a common camera.
At present, fisheye image correction methods can be divided into two categories, namely fisheye lens distortion correction methods based on calibration and correction methods based on projection transformation models, according to whether the fisheye image correction methods need to be calibrated or not. The calibration-based correction method mainly calibrates the internal and external parameters of the fisheye lens by setting calibration blocks, such as checkerboards, concentric circles, dot matrix templates and the like, and corrects the fisheye image on the basis of obtaining the internal and external parameters of the lens, but the method needs to perform complicated experiments and function calculation around a plurality of parameters, and the solved parameters are closely related to the type of the fisheye lens. The correction method based on the projection transformation model is to establish a mathematical model according to the imaging principle of perspective projection and restore a distorted image into a perspective projection image which accords with the habit of human vision by finding out the mapping relation between a fish-eye image and a target image, but the method is large in calculation amount and complex in process and is difficult to meet the detection application requirements.
The fisheye image correction model based on the longitude coordinates, namely the longitude correction model describes the function corresponding relation between the coordinates of the pixel points in the fisheye image and the coordinates of the pixel points in the corrected image. The longitude correction model transforms the abscissa of the pixel in the fisheye image to the original position and does not change the ordinate during correction, thereby transforming the circular fisheye image effective area to a square. However, for fisheye images with different distortion degrees, because the radius of the effective area of the fisheye image is a fixed value, at this time, adaptation adjustment cannot be performed according to the distortion of the fisheye image, and a relatively serious over-correction or insufficient correction degree may occur after correction is performed by using a longitude correction model. And the model only corrects the distortion in the longitudinal direction, and the distortion in the transverse direction is still very serious.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a fisheye image rapid correction method based on a distortion stretching factor, which can effectively correct the distortion of fisheye images and improve the correction speed and the correction quality of the fisheye images.
In order to achieve the purpose, the invention adopts the following technical scheme:
a fisheye image fast correction method based on distortion and stretching factors comprises the following steps:
step 1: extracting an effective area of the fisheye image;
step 2: establishing a correction optimization model on the basis of a longitude correction model, wherein a distortion stretching factor for eliminating the radial distortion influence is introduced into the correction optimization model (namely establishing a fisheye image correction model based on the distortion stretching factor);
and step 3: determining the value of a distortion stretching factor in the correction optimization model, and then establishing a mapping relation between pixel coordinates in a blank correction image and sub-pixel coordinates of an effective region of a fisheye image;
and 4, step 4: and generating a corresponding correction image of the fisheye image according to the established mapping relation.
Preferably, the step 1 specifically comprises the following steps: and determining the boundary of the effective area of the fisheye image by adopting a brightness threshold judgment method, and then calculating the circle center and the radius of the effective area of the fisheye image to obtain the distortion center and the distortion radius of the fisheye image.
Preferably, in step 2, the longitude correction model is expressed as:
wherein (x)0,y0) The distortion center coordinate of the fisheye image in the pixel coordinate system, (x, y) the pixel coordinate of the fisheye image in the pixel coordinate system, (u, v) the pixel coordinate of the corrected image in the pixel coordinate system, and R the distortion radius of the fisheye image.
Preferably, in step 2, the correction optimization model is expressed as:
where k is the distortion stretch factor.
Preferably, in the step 3, the value of the distortion stretch factor is determined by performing numerical solution by using an implicit expression of the distortion stretch factor.
Preferably, in step 3, the value of the distortion stretch factor is determined by selecting a value from the default interval [1.12,1.56 ].
Preferably, the step 4 specifically includes the following steps: and performing gray interpolation after coordinate mapping between pixel coordinates in the blank corrected image and sub-pixel coordinates of the effective area of the fisheye image is completed.
Preferably, the grayscale interpolation is an inverse interpolation method of backward mapping.
A fisheye image rapid correction system based on distortion and stretching factors comprises a fisheye image extraction module, a blank image establishing module, a coordinate mapping module and a blank image pixel assignment module;
the fisheye image extraction module is used for reading an input fisheye image and extracting an effective area of the fisheye image;
the blank image establishing module is used for generating a blank correction image according to the correction optimization model;
the coordinate mapping module is used for establishing a mapping relation between pixel coordinates in a blank corrected image and sub-pixel coordinates of an effective area of a fisheye image after determining the value of a distortion stretching factor in the correction optimization model;
and the blank image pixel assignment module is used for generating a corresponding correction image of the fisheye image according to the mapping relation.
The invention has the beneficial effects that:
the fisheye image correction method is based on a longitude correction model, introduces distortion stretching factors, and performs fisheye image correction in the transverse direction and the longitudinal direction on the basis of considering the radial distortion influence. Compared with the traditional fisheye image correction method based on longitude coordinates, the fisheye image correction method based on longitude coordinates has the characteristics of simple algorithm, strong real-time performance and easiness in transplanting of embedded equipment and mobile equipment, and the corrected image has small difference with a real scene and good correction effect.
Furthermore, the invention has the flexibility of improving the precision under the condition of not obviously improving the correction complexity. In the occasion that the parameter can be determined, only one parameter of the distortion tensile factor needs to be adjusted according to the solving result so as to improve the correction accuracy; in the case of difficult parameter determination, the value selection can be performed by using the set parameter default value to improve the correction accuracy.
Drawings
Fig. 1 is a flowchart of a fisheye image fast correction method based on distortion and stretching factor in the embodiment of the invention.
Fig. 2 is a schematic diagram of establishing a longitude correction model according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. The examples are given solely for the purpose of illustration and are not intended to limit the scope of the invention.
Example 1
As shown in fig. 1, the method for quickly correcting a fisheye image based on a distortion and stretching factor provided by the present invention is a method for adaptively correcting a fisheye image by adding a distortion and stretching factor to a longitude correction model, and includes the following steps:
step 1, extracting an effective area of the fisheye image.
Calculating the pixel brightness value I (x, y) of a fish-eye image pixel point:
I(x,y)＝0.59r(x,y)+0.11g(x,y)+0.3b(x,y)
wherein r (x, y), g (x, y), b (x, y) are the red, green, blue three-color component of the pixel point with coordinate (x, y) in the fish-eye image respectively.
Setting a threshold value T, wherein the threshold value T is used for judging the boundary of the effective area of the fisheye image, and the value of T is between 20 and 50. Reading pixel brightness values of the 1 st, 2 nd and 3 … columns of pixel points on the left side of the fisheye image until the pixel brightness value of one pixel point in a scanned (column-by-column read) current column is larger than T, continuously reading the pixel brightness value of the next column of pixel points, considering that the left boundary of the fisheye image effective area is scanned (the previous column is used as the left boundary of the effective area) when the pixel brightness value of the pixel point adjacent to the pixel point with the pixel brightness value larger than T in the previous column in the column is still larger than T, respectively obtaining the left, right, upper and lower boundaries of the fisheye image effective area according to the method, sequentially calculating the distances between the boundaries and the pixel points at the lower left corner of the fisheye image, and marking the results as left, right, top and bottom respectively.
In this case, the distortion radius R and the distortion center coordinate (x) of the fisheye image can be directly written0,y0) Thereby determining the circular fish-eye image effective area:
and 2, under the influence of radial distortion, establishing and solving a distortion correction model so as to describe the relationship among distortion center coordinates under a fisheye image pixel coordinate system, effective area pixel coordinates under the fisheye image pixel coordinate system and pixel coordinates under the pixel coordinate system of the corrected image.
And 2.1, establishing a fisheye image correction model based on the longitude coordinates.
In the longitude map, the equation for the pixel coordinates is:
x2+y2＝R2
where R is the radius of the longitude circle.
Referring to fig. 2, in the establishment of the longitude correction model, it is assumed that an arbitrary point a (x, y) on the image before correction is changed into a point B (u, v) on the image after correction by correction, and the projections of the two points on the zero latitude line are respectively C (x, y)0) And D (u, y)0) And the center of the effective area is known as O (x)0,y0) The radius is R, and can be obtained according to the Pythagorean theorem:
a longitude correction model can further be derived:
step 2.2 introduces a distortion stretch factor k.
The radial distortion of the fisheye image is that pixel points in the image use a distortion center as a central point to generate position deviation along the radial direction, so that the scenery in the image is deformed. The radial distortion of the image is the most main distortion caused by the imaging process of the fisheye lens, and is also the distortion which has the largest influence on the correction of the imaging result, and the formula is expressed as follows:
wherein, (u, v) is the pixel point coordinate under the pixel coordinate system of the corrected image, (x, y) is the pixel point coordinate under the pixel coordinate system of the fish eye image, r is the distance from the distortion point to the central point, r is the distortion point2＝x2+y2；δx(x, y) and δy(x, y) being x-axis and y-axis, respectivelyAn amount of distortion; k is a radical ofnIs distortion coefficient (n ═ 1,2,3, …; k1Is a low order term, k2、k3… is a high order term).
The invention proposes a distortion stretching factor k on the basis of considering the influence of radial distortion, and the distortion stretching factor k means that the distance from all points in an image to the center of the image is stretched by k times.
And 2.3, establishing a fisheye image correction model based on the distortion stretching factor.
On the basis of the longitude coordinate model, a fisheye image distortion correction model is established by adding a distortion stretching factor k:
step 2.4 calculates the distortion stretch factor.
According to the formula in step 2.2, let OA ═ k × R, and omit the high-order term that has little influence on distortion, and obtain:
k*OA＝OB(1+k1OB2)
the formula for the distance between two points is:
further elaboration may yield an implicit expression for k:
wherein
Carrying out specific numerical solution by bringing in a fisheye image to be corrected (namely the fisheye image effective area obtained in the step 1); and adjusting the value of k according to the actual situation, so as to obtain a final fisheye image distortion correction model and a mapping relation according to the value of the distortion stretching factor on the basis of correcting a distortion curve (meridian) with distorted boundaries in the image into a straight line.
And 3, providing a blank correction image according to the fisheye image distortion correction model (the blank correction image is matched with the fisheye image to be corrected, and the blank correction image is slightly larger than the fisheye image to be corrected), and establishing a mapping relation between pixel point coordinates in the blank correction image and sub-pixel coordinates in the fisheye image to be corrected, so as to complete coordinate mapping.
And 4, performing gray interpolation after coordinate mapping is completed to obtain a corrected image.
Specifically, the sub-pixel coordinates in the fisheye image to be corrected, which have a mapping relation with the pixel points of the blank corrected image, are subjected to backward mapping reverse interpolation to obtain sub-pixel values, and the obtained sub-pixel values are assigned to the corresponding pixel points in the blank corrected image. Therefore, the edge loss of the image (namely the corrected image) obtained after the fisheye image is corrected is less.
Example 2
In consideration of the size of the image to be corrected after extracting the effective region, | x-x at this time0I and y-y0Generally, the value of k is calculated by substituting special points (left vertex, right vertex, upper vertex and lower vertex of the image) in the image between 350 and 550, and the calculated value of k after averaging is between 1.12 and 1.56, which is in accordance with the actual requirement (for example, k is 1.2), so that the default value interval of k is determined, and higher correction accuracy can be ensured by adjusting k while simplifying the correction process.
Claims (9)
1. A fisheye image fast correction method based on distortion and stretching factors is characterized in that: the method comprises the following steps:
1) extracting an effective area of the fisheye image;
2) establishing a correction optimization model on the basis of the longitude correction model, wherein a distortion stretching factor for eliminating the influence of radial distortion is introduced into the correction optimization model;
3) determining the value of a distortion stretching factor in the correction optimization model, and then establishing a mapping relation between pixel coordinates in a blank correction image and sub-pixel coordinates of an effective region of a fisheye image;
4) and generating a corresponding correction image of the fisheye image according to the established mapping relation.
2. The method for rapidly correcting the fisheye image based on the distorted stretching factor as claimed in claim 1, wherein: the step 1 specifically comprises the following steps: and determining the boundary of the effective area of the fisheye image by adopting a brightness threshold judgment method, and then calculating the circle center and the radius of the effective area of the fisheye image to obtain the distortion center and the distortion radius of the fisheye image.
3. The method for rapidly correcting the fisheye image based on the distorted stretching factor as claimed in claim 1, wherein: in step 2, the longitude correction model is expressed as:
wherein (x)0,y0) The distortion center coordinate of the fisheye image in the pixel coordinate system, (x, y) the pixel coordinate of the fisheye image in the pixel coordinate system, (u, v) the pixel coordinate of the corrected image in the pixel coordinate system, and R the distortion radius of the fisheye image.
4. The method for rapidly correcting the fisheye image based on the distortion tension factor as claimed in claim 1 or 3, characterized in that: in step 2, the correction optimization model is expressed as:
wherein (x)0,y0) Is distortion center coordinate under fish-eye image pixel coordinate system, (x, y) is pixel point coordinate under fish-eye image pixel coordinate system, (u, v) is pixel point coordinate under corrected image pixel coordinate system, R is distortion radius of fish-eye imageK is the distortion stretch factor.
5. The method for rapidly correcting the fisheye image based on the distorted stretching factor as claimed in claim 1, wherein: in the step 3, the value of the distortion stretch factor is determined by performing numerical solution by using an implicit expression of the distortion stretch factor.
6. The method for rapidly correcting the fisheye image based on the distorted stretching factor as claimed in claim 1, wherein: in step 3, the value of the distortion stretch factor is determined by selecting a value from the default interval [1.12,1.56 ].
7. The method for rapidly correcting the fisheye image based on the distorted stretching factor as claimed in claim 1, wherein: the step 4 specifically comprises the following steps: and performing gray interpolation after coordinate mapping between pixel coordinates in the blank corrected image and sub-pixel coordinates of the effective area of the fisheye image is completed.
8. The method of claim 7, wherein the fisheye image fast correction method based on the distortion tension factor is characterized in that: the gray level interpolation adopts a backward mapping reverse interpolation method.
9. The utility model provides a fisheye image fast correction system based on distortion tension factor which characterized in that: the fisheye image processing system comprises a fisheye image extraction module, a blank image establishing module, a coordinate mapping module and a blank image pixel assignment module;
the fisheye image extraction module is used for reading an input fisheye image and extracting an effective area of the fisheye image;
the blank image establishing module is used for generating a blank corrected image according to the correction optimization model, and the correction optimization model is established on the basis of the longitude correction model and introduces a distortion stretching factor for eliminating the influence of radial distortion;
the coordinate mapping module is used for establishing a mapping relation between pixel coordinates in a blank corrected image and sub-pixel coordinates of an effective area of a fisheye image after determining the value of a distortion stretching factor in the correction optimization model;
and the blank image pixel assignment module is used for generating a corresponding correction image of the fisheye image according to the mapping relation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210062723.9A CN114331826A (en) | 2022-01-19 | 2022-01-19 | Fisheye image rapid correction method based on distortion tension factor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210062723.9A CN114331826A (en) | 2022-01-19 | 2022-01-19 | Fisheye image rapid correction method based on distortion tension factor |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114331826A true CN114331826A (en) | 2022-04-12 |
Family
ID=81028374
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210062723.9A Pending CN114331826A (en) | 2022-01-19 | 2022-01-19 | Fisheye image rapid correction method based on distortion tension factor |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114331826A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114820289A (en) * | 2022-05-06 | 2022-07-29 | 北京航空航天大学 | Fisheye image correction method based on radial symmetric projection model |
| CN114820289B (en) * | 2022-05-06 | 2024-08-02 | 北京航空航天大学 | Fisheye image correction method based on radial symmetric projection model |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090141148A1 (en) * | 2007-12-04 | 2009-06-04 | Kosuke Imamura | Distortion-corrected image generation unit and distortion-corrected image generation method |
| CN102298771A (en) * | 2011-08-16 | 2011-12-28 | 淮安盈科伟力科技有限公司 | Fish-eye image rapid correction method of panoramic parking auxiliary system |
| KR20140072470A (en) * | 2012-12-05 | 2014-06-13 | 광운대학교 산학협력단 | Distorted Image Processing Method For Fish-Eye Lens |
| CN103996173A (en) * | 2014-05-09 | 2014-08-20 | 东北大学 | Fisheye image correction method based on changed long axis ellipse fitting |
| CN104574289A (en) * | 2013-10-29 | 2015-04-29 | 深圳市中航比特通讯技术有限公司 | Fish-eye image distortion correction algorithm based on ellipsoidal model |
| CN106815805A (en) * | 2017-01-17 | 2017-06-09 | 湖南优象科技有限公司 | Rapid distortion bearing calibration based on Bayer images |
| CN107665483A (en) * | 2017-09-27 | 2018-02-06 | 天津智慧视通科技有限公司 | Exempt from calibration easily monocular camera lens fish eye images distortion correction method |
-
2022
- 2022-01-19 CN CN202210062723.9A patent/CN114331826A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090141148A1 (en) * | 2007-12-04 | 2009-06-04 | Kosuke Imamura | Distortion-corrected image generation unit and distortion-corrected image generation method |
| CN102298771A (en) * | 2011-08-16 | 2011-12-28 | 淮安盈科伟力科技有限公司 | Fish-eye image rapid correction method of panoramic parking auxiliary system |
| KR20140072470A (en) * | 2012-12-05 | 2014-06-13 | 광운대학교 산학협력단 | Distorted Image Processing Method For Fish-Eye Lens |
| CN104574289A (en) * | 2013-10-29 | 2015-04-29 | 深圳市中航比特通讯技术有限公司 | Fish-eye image distortion correction algorithm based on ellipsoidal model |
| CN103996173A (en) * | 2014-05-09 | 2014-08-20 | 东北大学 | Fisheye image correction method based on changed long axis ellipse fitting |
| CN106815805A (en) * | 2017-01-17 | 2017-06-09 | 湖南优象科技有限公司 | Rapid distortion bearing calibration based on Bayer images |
| CN107665483A (en) * | 2017-09-27 | 2018-02-06 | 天津智慧视通科技有限公司 | Exempt from calibration easily monocular camera lens fish eye images distortion correction method |
Non-Patent Citations (3)
| Title |
|---|
| 刘亿静;苗长云;杨彦利;: "基于经纬映射的径向畸变快速校正算法的研究", 激光杂志, no. 01, 25 January 2015 (2015-01-25) * |
| 周小康;饶鹏;朱秋煜;陈忻;: "鱼眼图像畸变校正技术研究", 工业控制计算机, no. 10, 25 October 2017 (2017-10-25) * |
| 涂治洲: "针对鱼眼图像边缘校正失真的快速校正算法", 电子测量技术, vol. 45, no. 15, 31 August 2022 (2022-08-31) * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114820289A (en) * | 2022-05-06 | 2022-07-29 | 北京航空航天大学 | Fisheye image correction method based on radial symmetric projection model |
| CN114820289B (en) * | 2022-05-06 | 2024-08-02 | 北京航空航天大学 | Fisheye image correction method based on radial symmetric projection model |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110197466B (en) | Wide-angle fisheye image correction method | |
| CN110889829B (en) | Monocular distance measurement method based on fish eye lens | |
| CN107665483B (en) | Calibration-free convenient monocular head fisheye image distortion correction method | |
| CN107424118A (en) | Based on the spherical panorama mosaic method for improving Lens Distortion Correction | |
| CN111199528A (en) | Fisheye image distortion correction method | |
| CN108022223B (en) | Tone mapping method based on logarithm mapping function blocking processing fusion | |
| CN107993263A (en) | Viewing system automatic calibration method, automobile, caliberating device and storage medium | |
| CN103996173B (en) | A kind of fisheye image correcting method based on elongated axle ellipse fitting | |
| CN107689033B (en) | Fisheye image distortion correction method based on ellipse segmentation | |
| CN106447602A (en) | Image mosaic method and device | |
| CN112669394A (en) | Automatic calibration method for vision detection system | |
| CN107633489A (en) | The fish eye lens center of circle, which is brought up again, takes reflection method distortion correction method | |
| CN106600549A (en) | Method and device for correcting fisheye image | |
| CN108154536A (en) | The camera calibration method of two dimensional surface iteration | |
| CN115239820A (en) | Split type flying vehicle aerial view real-time splicing and parking space detection method | |
| CN115049535B (en) | Fisheye lens effective area acquisition and image fine correction method | |
| CN110942475B (en) | Ultraviolet and visible light image fusion system and rapid image registration method | |
| CN115883755A (en) | Multi-exposure image fusion method under multi-type scene | |
| CN113706607B (en) | Subpixel positioning method, computer equipment and device based on circular array diagram | |
| CN108198222B (en) | Wide-angle lens calibration and image correction method | |
| CN111860632B (en) | Multipath image consistency fusion method | |
| CN117097872A (en) | Automatic trapezoid correction system and method for projection equipment | |
| CN114331826A (en) | Fisheye image rapid correction method based on distortion tension factor | |
| CN115100078B (en) | Method and related device for correcting and filling dot matrix coordinates in curved screen image | |
| CN112085803B (en) | Multi-lens multi-detector spliced camera color consistency processing method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20240703 Address after: 518000 1104, Building A, Zhiyun Industrial Park, No. 13, Huaxing Road, Henglang Community, Longhua District, Shenzhen, Guangdong Province Applicant after: Shenzhen Hongyue Information Technology Co.,Ltd. Country or region after: China Address before: 710021 Shaanxi province Xi'an Weiyang University Park Applicant before: SHAANXI University OF SCIENCE & TECHNOLOGY Country or region before: China |